Benjamin Guedj

104 papers A* 13A 6B 2Journal 78Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters. CoRR Dominic Weisser, Chloé Hashimoto-Cullen, Benjamin Guedj
2025	B	`conf`	A PAC-Bayesian Link Between Generalisation and Flat Minima. ALT Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj
2025	B	`conf`	Generalisation under gradient descent via deterministic PAC-Bayes. ALT Eugenio Clerico, Tyler Farghly, George Deligiannidis, Benjamin Guedj, Arnaud Doucet
2025	J	`jnl`	Generalization Bounds: Perspectives from Information Theory and PAC-Bayes. Found. Trends Mach. Learn. Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj, Maxim Raginsky
2025	J	`jnl`	How good is PAC-Bayes at explaining generalisation? CoRR Antoine Picard-Weibel, Eugenio Clerico, Roman Moscoviz, Benjamin Guedj
2025	J	`jnl`	Non-Vacuous Generalization Bounds: Can Rescaling Invariances Help? CoRR Damien Rouchouse, Antoine Gonon, Rémi Gribonval, Benjamin Guedj
2025	J	`jnl`	RestoreAI - Pattern-based Risk Estimation Of Remaining Explosives. CoRR Björn Kischelewski, Benjamin Guedj, David Wahl
2024	J	`jnl`	A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj
2024	J	`jnl`	A note on regularised NTK dynamics with an application to PAC-Bayesian training. Trans. Mach. Learn. Res. Eugenio Clerico, Benjamin Guedj
2024	J	`jnl`	AI for ERW Detection in Clearance Operations - The State of Research. CoRR Björn Kischelewski, Gregory Cathcart, David Wahl, Benjamin Guedj
2024	J	`jnl`	Closed-form Filtering for Non-linear Systems. CoRR Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2024	A	`conf`	Comparing Comparators in Generalization Bounds. AISTATS Fredrik Hellström, Benjamin Guedj
2024	A*	`conf`	Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound. NeurIPS Reuben Adams, John Shawe-Taylor, Benjamin Guedj
2024	A*	`conf`	Learning via Surrogate PAC-Bayes. NeurIPS Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj
2024	J	`jnl`	Learning via Surrogate PAC-Bayes. CoRR Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj
2024	J	`jnl`	Predicting Electricity Consumption with Random Walks on Gaussian Processes. CoRR Chloé Hashimoto-Cullen, Benjamin Guedj
2024	J	`jnl`	Tighter Generalisation Bounds via Interpolation. CoRR Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2023	J	`jnl`	A note on regularised NTK dynamics with an application to PAC-Bayesian training. CoRR Eugenio Clerico, Benjamin Guedj
2023	J	`jnl`	Cluster-Specific Predictions with Multi-Task Gaussian Processes. J. Mach. Learn. Res. Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey
2023	J	`jnl`	Comparing Comparators in Generalization Bounds. CoRR Fredrik Hellström, Benjamin Guedj
2023	J	`jnl`	Federated Learning with Nonvacuous Generalisation Bounds. CoRR Pierre Jobic, Maxime Haddouche, Benjamin Guedj
2023	J	`jnl`	Generalization Bounds: Perspectives from Information Theory and PAC-Bayes. CoRR Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj, Maxim Raginsky
2023	A*	`conf`	Learning via Wasserstein-Based High Probability Generalisation Bounds. NeurIPS Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2023	J	`jnl`	Learning via Wasserstein-Based High Probability Generalisation Bounds. CoRR Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2023	J	`jnl`	MMD Aggregated Two-Sample Test. J. Mach. Learn. Res. Antonin Schrab, Ilmun Kim, Mélisande Albert, Béatrice Laurent, Benjamin Guedj, Arthur Gretton
2023	J	`jnl`	Model validation using mutated training labels: An exploratory study. Neurocomputing Jie M. Zhang, Mark Harman, Benjamin Guedj, Earl T. Barr, John Shawe-Taylor
2023	J	`jnl`	Optimistic Dynamic Regret Bounds. CoRR Maxime Haddouche, Benjamin Guedj, Olivier Wintenberger
2023	J	`jnl`	PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales. Trans. Mach. Learn. Res. Maxime Haddouche, Benjamin Guedj
2023	A	`conf`	Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty. AISTATS Felix Biggs, Benjamin Guedj
2023	J	`jnl`	Wasserstein PAC-Bayes Learning: A Bridge Between Generalisation and Optimisation. CoRR Maxime Haddouche, Benjamin Guedj
2022	J	`jnl`	A PAC-Bayes bound for deterministic classifiers. CoRR Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet
2022	J	`jnl`	Controlling Confusion via Generalisation Bounds. CoRR Reuben Adams, John Shawe-Taylor, Benjamin Guedj
2022	J	`jnl`	Depolarising Social Networks: Optimisation of Exposure to Adverse Opinions in the Presence of a Backfire Effect. CoRR Antoine Vendeville, Benjamin Guedj, Shi Zhou
2022	A*	`conf`	Efficient Aggregated Kernel Tests using Incomplete $U$-statistics. NeurIPS Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton
2022	J	`jnl`	Efficient Aggregated Kernel Tests using Incomplete U-statistics. CoRR Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton
2022	A*	`conf`	KSD Aggregated Goodness-of-fit Test. NeurIPS Antonin Schrab, Benjamin Guedj, Arthur Gretton
2022	J	`jnl`	KSD Aggregated Goodness-of-fit Test. CoRR Antonin Schrab, Benjamin Guedj, Arthur Gretton
2022	J	`jnl`	MAGMA: inference and prediction using multi-task Gaussian processes with common mean. Mach. Learn. Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey
2022	A*	`conf`	Measuring dissimilarity with diffeomorphism invariance. ICML Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2022	J	`jnl`	Measuring dissimilarity with diffeomorphism invariance. CoRR Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2022	A*	`conf`	Non-Vacuous Generalisation Bounds for Shallow Neural Networks. ICML Felix Biggs, Benjamin Guedj
2022	J	`jnl`	Non-Vacuous Generalisation Bounds for Shallow Neural Networks. CoRR Felix Biggs, Benjamin Guedj
2022	A	`conf`	On Margins and Derandomisation in PAC-Bayes. AISTATS Felix Biggs, Benjamin Guedj
2022	A*	`conf`	On Margins and Generalisation for Voting Classifiers. NeurIPS Felix Biggs, Valentina Zantedeschi, Benjamin Guedj
2022	J	`jnl`	On Margins and Generalisation for Voting Classifiers. CoRR Felix Biggs, Valentina Zantedeschi, Benjamin Guedj
2022	A	`conf`	On PAC-Bayesian reconstruction guarantees for VAEs. AISTATS Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj
2022	J	`jnl`	On PAC-Bayesian reconstruction guarantees for VAEs. CoRR Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj
2022	J	`jnl`	On change of measure inequalities for f-divergences. CoRR Antoine Picard-Weibel, Benjamin Guedj
2022	A*	`conf`	Online PAC-Bayes Learning. NeurIPS Maxime Haddouche, Benjamin Guedj
2022	J	`jnl`	Online PAC-Bayes Learning. CoRR Maxime Haddouche, Benjamin Guedj
2022	—	`conf`	Opening up Echo Chambers via Optimal Content Recommendation. COMPLEX NETWORKS (1) Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj
2022	J	`jnl`	Opening up echo chambers via optimal content recommendation. CoRR Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj
2022	J	`jnl`	PAC-Bayes with Unbounded Losses through Supermartingales. CoRR Maxime Haddouche, Benjamin Guedj
2022	J	`jnl`	Reprint: a randomized extrapolation based on principal components for data augmentation. CoRR Jiale Wei, Qiyuan Chen, Pai Peng, Benjamin Guedj, Le Li
2022	J	`jnl`	Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty. CoRR Felix Biggs, Benjamin Guedj
2021	J	`jnl`	Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks. Entropy Felix Biggs, Benjamin Guedj
2021	J	`jnl`	Forecasting elections results via the voter model with stubborn nodes. Appl. Netw. Sci. Antoine Vendeville, Benjamin Guedj, Shi Zhou
2021	J	`jnl`	Learning PAC-Bayes Priors for Probabilistic Neural Networks. CoRR María Pérez-Ortiz, Omar Rivasplata, Benjamin Guedj, Matthew Gleeson, Jingyu Zhang, John Shawe-Taylor, Miroslaw Bober, Josef Kittler
2021	A*	`conf`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	J	`jnl`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	J	`jnl`	MMD Aggregated Two-Sample Test. CoRR Antonin Schrab, Ilmun Kim, Mélisande Albert, Béatrice Laurent, Benjamin Guedj, Arthur Gretton
2021	J	`jnl`	On Margins and Derandomisation in PAC-Bayes. CoRR Felix Biggs, Benjamin Guedj
2021	A	`conf`	Online k-means Clustering. AISTATS Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom
2021	J	`jnl`	PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses. Entropy Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
2021	J	`jnl`	Progress in Self-Certified Neural Networks. CoRR María Pérez-Ortiz, Omar Rivasplata, Emilio Parrado-Hernández, Benjamin Guedj, John Shawe-Taylor
2021	J	`jnl`	Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly. Entropy Le Li, Benjamin Guedj
2021	J	`jnl`	Still No Free Lunches: The Price to Pay for Tighter PAC-Bayes Bounds. Entropy Benjamin Guedj, Louis Pujol
2021	—	`conf`	Towards Control of Opinion Diversity by Introducing Zealots into a Polarised Social Group. COMPLEX NETWORKS Antoine Vendeville, Benjamin Guedj, Shi Zhou
2020	J	`jnl`	A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings. CoRR Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz, John Shawe-Taylor
2020	J	`jnl`	An end-to-end data-driven optimisation framework for constrained trajectories. CoRR Florent Dewez, Benjamin Guedj, Arthur Talpaert, Vincent Vandewalle
2020	J	`jnl`	Attributing and Referencing (Research) Software: Best Practices and Outlook From Inria. Comput. Sci. Eng. Pierre Alliez, Roberto Di Cosmo, Benjamin Guedj, Alain Girault, Mohand-Saïd Hacid, Arnaud Legrand, Nicolas P. Rougier
2020	J	`jnl`	Cluster-Specific Predictions with Multi-Task Gaussian Processes. CoRR Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey
2020	J	`jnl`	Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks. CoRR Felix Biggs, Benjamin Guedj
2020	J	`jnl`	Forecasting elections results via the voter model with stubborn nodes. CoRR Antoine Vendeville, Benjamin Guedj, Shi Zhou
2020	J	`jnl`	From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning. CoRR Florent Dewez, Benjamin Guedj, Vincent Vandewalle
2020	J	`jnl`	How opinions crystallise: an analysis of polarisation in the voter model. CoRR Antoine Vendeville, Benjamin Guedj, Shi Zhou
2020	J	`jnl`	Kernel-Based Ensemble Learning in Python. Inf. Benjamin Guedj, Bhargav Srinivasa Desikan
2020	J	`jnl`	MAGMA: Inference and Prediction with Multi-Task Gaussian Processes. CoRR Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey
2020	—	`conf`	Non-linear Aggregation of Filters to Improve Image Denoising. SAI (2) Benjamin Guedj, Juliette Rengot
2020	J	`jnl`	PAC-Bayes unleashed: generalisation bounds with unbounded losses. CoRR Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
2020	A*	`conf`	PAC-Bayesian Bound for the Conditional Value at Risk. NeurIPS Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
2020	J	`jnl`	PAC-Bayesian Bound for the Conditional Value at Risk. CoRR Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
2020	A	`conf`	PAC-Bayesian Contrastive Unsupervised Representation Learning. UAI Kento Nozawa, Pascal Germain, Benjamin Guedj
2020	—	`conf`	Revisiting Clustering as Matrix Factorisation on the Stiefel Manifold. LOD (1) Stéphane Chrétien, Benjamin Guedj
2020	J	`jnl`	Upper and Lower Bounds on the Performance of Kernel PCA. CoRR Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
2019	J	`jnl`	A Primer on PAC-Bayesian Learning. CoRR Benjamin Guedj
2019	J	`jnl`	Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria. CoRR Pierre Alliez, Roberto Di Cosmo, Benjamin Guedj, Alain Girault, Mohand-Said Hacid, Arnaud Legrand, Nicolas P. Rougier
2019	—	`conf`	Decentralized Learning with Budgeted Network Load Using Gaussian Copulas and Classifier Ensembles. PKDD/ECML Workshops (1) John Klein, Mahmoud Albardan, Benjamin Guedj, Olivier Colot
2019	A*	`conf`	Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks. NeurIPS Gaël Letarte, Pascal Germain, Benjamin Guedj, François Laviolette
2019	J	`jnl`	Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks. CoRR Gaël Letarte, Pascal Germain, Benjamin Guedj, François Laviolette
2019	J	`jnl`	Kernel-Based Ensemble Learning in Python. CoRR Benjamin Guedj, Bhargav Srinivasa Desikan
2019	J	`jnl`	Non-linear aggregation of filters to improve image denoising. CoRR Benjamin Guedj, Juliette Rengot
2019	J	`jnl`	Online k-means Clustering. CoRR Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom
2019	A*	`conf`	PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
2019	J	`jnl`	PAC-Bayes Un-Expected Bernstein Inequality. CoRR Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj
2019	J	`jnl`	PAC-Bayesian Contrastive Unsupervised Representation Learning. CoRR Kento Nozawa, Pascal Germain, Benjamin Guedj
2019	J	`jnl`	Perturbed Model Validation: A New Framework to Validate Model Relevance. CoRR Jie M. Zhang, Earl T. Barr, Benjamin Guedj, Mark Harman, John Shawe-Taylor
2019	J	`jnl`	Revisiting clustering as matrix factorisation on the Stiefel manifold. CoRR Stéphane Chrétien, Benjamin Guedj
2019	J	`jnl`	Still no free lunches: the price to pay for tighter PAC-Bayes bounds. CoRR Benjamin Guedj, Louis Pujol
2018	J	`jnl`	Decentralized learning with budgeted network load using Gaussian copulas and classifier ensembles. CoRR John Klein, Mahmoud Albardan, Benjamin Guedj, Olivier Colot
2018	J	`jnl`	Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly. CoRR Benjamin Guedj, Le Li
2018	J	`jnl`	Simpler PAC-Bayesian bounds for hostile data. Mach. Learn. Pierre Alquier, Benjamin Guedj
2017	J	`jnl`	Pycobra: A Python Toolbox for Ensemble Learning and Visualisation. J. Mach. Learn. Res. Benjamin Guedj, Bhargav Srinivasa Desikan
2016	J	`jnl`	COBRA: A combined regression strategy. J. Multivar. Anal. Gérard Biau, Aurélie Fischer, Benjamin Guedj, James D. Malley